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9th European Conference on the Mathematics of Oil Recovery — Cannes, France, 30 August - 2 September 2004

Abstract The compressional acoustic waves in carbonates are assumed to travel primarily through the rock matrix, and fluid does not play much of role. Extensive study has established the relationship between changes in acoustic property with saturation in clastics. However, little is proposed for the interpretation of the Vp/Vs ratio in carbonates. Various studies like Li et. al., 2003 and Eberli et. al.’ 2003 and Alain Brie ‘, 2001 were published to monitor the changes in Vp/Vs ration with respect to saturation for heterogeneous carbonates. Alain Brie developed a methodology to interpret the sonic slowness responses in carbonates based on a micro structural model using the Kuster-Toksoz formulation with pore inclusions of three different shapes. For practical implementation Brie developed an empirical formula that relates the dry frame Vp/Vs to porosity in carbonates with the help of an additional parameter, spf (spherical porosity contribution), to account for the heterogeneity of the reservoir. This paper aims to estimate the change in sonic and seismic behavior with change in saturation for a carbonate reservoir using Brie’s methodology. The reservoir rock is primarily limestone with porosity ranging from 15 to –25 p.u. The total porosity is a combination of vuggy porosity and intergranular porosity. The field-scale core calibrated porosity analysis for this reservoir from electrical imaging data (Tyagi et al. 2002) shows the presence of dual porosity as shown in Fig. 1. Moreover, the fracture analysis using data from DSI* acquired in a horizontal well, also shows the presence of fractures as shown in Fig. 2. Both the analysis indicates that the porosity of the reservoir is heterogeneous in nature. The indications of the presence of heterogeneous porosity due to vugs and fractures along with availability of Brie’s technique have motivated us to analyze the effect of saturation change on seismic signatures as confidence building step for a 4-D study conducted in the reservoir. The analysis is carried out in three steps:

1) Sensitivity analysis of acoustic properties due to change in saturation.

2) Fluid replacement to predict the change in acoustic properties caused by change in saturation

3) Analysis of modeled versus observed AVO response.

The observed AVO response (intercept and gradient) for water and gas bearing reservoir conditions show very good match with modeled results. However, the observed intercept and gradient for oil bearing conditions does not show same degree of agreement with modeled behavior

P010 MODELING THE EFFECT OF SATURATION CHANGE ON SEISMIC SIGNATURE FOR CARBONATE RESERVOIRS

BABAN JEE*, ANIL KUMAR TYAGI**, PRAMESH TYAGI***

*ONGC, Vasudhara Bhawan, Bandra, Mumbai, ** Reliance Industries Limited E & P(Petroleum), DAKC, Koparkhairane, Mumbai

** Schlumberger, NSE Estate, WE Highway, Goregaon(E), Mumbai

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Sensitivity Analysis

The compressional slowness (DT) vs saturation and density vs saturation for 11 platform wells was analyzed using a 10% cutoff criteria for clay content and shown in fig 3a&3b. The analysis showed that the acoustic properties of this reservoir are sensitive to change in saturation. In the entire field only two wells PN-D-1 (Gas bearing) and PN-D-2 (Oil bearing) had compressional and shear slowness measurement. Fig. 4a and 4b is a cross plot between Vp/Vs and porosity and DT and Vp/Vs respectively showing the data points for both the wells. The Vp/Vs ratio for water bearing, oil bearing, and gas bearing limestone is distinctly different for the same porosity and have values of ~1.92 , ~ 1.78, and 1.65 respectively.

Fluid replacement The fluid replacement modeling is carried out using Brie’s methodology for an oil-bearing well (PN-D-2) of the reservoir and the logs are estimated for water- and gas-bearing conditions for the sonic and seismic domains. Figure 5a & 5b shows cross plots between Vp/Vs and effective porosity for observed data in well PN-D-1-a gas bearing well and fluid replaced data in well PN-D-2- an oil bearing well respectively. To simulate a case equivalent to PN-D-1 only the oil of PN-D-2 is replaced with gas. There is striking similarity of cluster distribution between gas modeled PN-D-2 and observed gas well PN-D-1.

The results suggest that for a highly porous (porosity>25%) and heterogeneous (spf ~20%) limestone reservoir in the sonic domain, the expected increase in the Vp/Vs, is 7% if all the pore fluid, i.e., oil + water (gas/oil ratio ~ 140), is replaced by water. The expected decrease in Vp/Vs is 7% if all the pore fluid i.e. oil+water is replaced by gas. In the seismic domain, the changes are 7% and 10%, respectively. The seismic domain results could not be verified in absence of measured shear velocity from seismic data. However, the same has been tried through comparison of modeled vs observed AVA/AVO response.

Analysis of Modeled vs Observed AVA/AVO We did following three exercises after estimating the logs in seismic domain:

1. Model AVO response using modeled logs (Seismic) of PN-D-2 for 100% water bearing reservoir condition and compare with observed AVO response of water bearing well PN-D-3,4,5.

2. Model AVO response using modeled logs (Sonic and Seismic) of PN-D-2 for oil+water bearing reservoir condition and compare with observed AVO response of oil+water bearing well i.e. PN-D-2.

3. Model AVO response using modeled logs (Sonic and Seismic) of PN-D-2 for gas+water (Oil replaced with gas) bearing reservoir condition and compare with observed AVO response of gas+water bearing well PN-D-1.

A two layered model is built wherein the upper layer is the shale (primarily Montmorrilonite) and lower layer is the limestone reservoir. Abovementioned five different conditions are simulated for AVA modeling using Zoeppritz equations. The modeling results shown in figure 6 demonstrate that the AVO of this reservoir is of class I/II with positive intercept and negative gradient. The intercept and gradient values for various scenarios are shown in fig. 6.

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9th European Conference on the Mathematics of Oil Recovery — Cannes, France, 30 August - 2 September 2004

Figure 7a & 7b show the area distribution of observed intercept and gradient respectively. The 3-D seismic data used for AVO processing is angle limited, maximum upto 30 degree. Therefore, the modeled AVA gradient upto 30 degree is considered for comparison. As predicted from AVA modeling there is a gradual decrease in intercept from well PN-D-5(water) PN-D-2(oil)

PN-D-1(gas); fig 7a. However, the observed intercept around PN-D-1(Fig7a) is mostly small positive tending to zero which matches with modeled AVA response for seismic domain(Fig 6). The behavior of observed gradient from well PN-D-5(water) PN-D-2(oil) PN-D-1(gas); figure 7b is also as per modeled behavior. Observed AVO attributes for other two water bearing wells, namely PN-D-3,&4, could not be analyzed as they lie in the area where the top of the reservoir is not resolved. The study establishes from field data that sonic slowness does change with saturation in carbonate reservoirs. It further establishes that seismic response of carbonate reservoir also changes with saturation under favorable conditions. The sequence of analysis adopted, from porosity partitioning from core calibrated electrical image data analysis to fluid replacement modeling and its link with seismic response, is critical for the success of 4-D seismic in carbonate reservoirs. References Brie, A., 2001. A micro-structural model for compressional and shear slowness interpretation in carbonates. 42 nd Annual Logging Symposium of the SPWLA. Eberli, G.P. et. al.. 2003. Factors controlling elastic properties in carbonate sediments and rocks, The Leading Edge, July 2003 Li, Y. et. al., 2003. Recent applications of AVO to carbonate reservoirs in the Western Canadian sedimentary Basin, The Leading Edge, July 2003 Picket,G.R.,1963, Acoustic character logs and their applications in formation evaluation, JPT, 659. Tyagi,A.K. et al; 2002, Porosity analysis using borehole electrical images in carbonate reservoirs, SPWLA

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F ig 1 : P o ro s ity H e te ro g e n e ity A n a lys is fro m FM I* F ig 2 : F ra c tu re a n a lys is u s in g D S I*

F ig 3a : D T vs S a tu ra tio n F ig 3 b : D e n s ity vs S a tu ra tio n

* M a rk o f S c h lu m b e rg e r

D a ta fo r 1 1P la tfo rm s

D a ta fo r 1 1P la tfo rm s

F i g 4 a : V p V s v s P o r o s i t y f o r w e l l P N - D - 1 a n d P N - D - 2 F ig 4 b : V p V s v s D T f o r w e l l P N - D - 1 a n d P N - D - 2

P N - D - 1 ( G A S )P N - D - 2 ( O I L )

G A S L i n e

O I L L i n e

H y d r o c a r b o n L i n e

F i g 5 a : O b s e r v e d V p V s v s e f f e c t iv e p o r o s i t y f o r w e l l P N - D - 1 F i g 5 b : M o d e le d V p V s v s E f f e c t i v e p o r o s i t y i n w e l l P N - D - 2

V p V s = 1 . 9

V p V s = 1 . 6 5

P N - D - 1 ( O B S E R V E D G A S ) P N - D - 2 ( O I L G A S )

P N - D - 1 ( G A S )P N - D - 2 ( O I L )

H y d r o c a r b o n B e a r i n gW a t e r B e a r i n gP o o r F a c i e s

H y d r o c a r b o n B e a r i n gW a t e r B e a r i n gP o o r F a c i e s

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9th European Conference on the Mathematics of Oil Recovery — Cannes, France, 30 August - 2 September 2004

F ig 6 :M od e led A V A at the top o f B asse in form a tion for var ious sce nar ios

A V A M od e lin g

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00 .10 .20 .3

0 1 0 2 0 3 0 4 0 4 5 5 0A n g e o f In c id e n c e

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O i l _ o bs @ S o n i c

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G a s @ s e i s m i c< --O i l _ o bs @ S o n i c

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Intercep t a nd G rad ie nt(30 d egree )W ater (0 .155 , -0 .22 )O il (0 .09 , -0 .30 )G as (0 .05 , -0 .36 )

F ig 7 a :O bserved In tercep t a t the top o f B asse in form a tion F ig 7b : O bserved G rad ie nt at the top o f B asse in form ation

P N -D -2

P N -D -1

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In te rcep t G rad ien t

P N -D -3

P N -D -4

P N -D -3

P N -D -4

P N -D -5 P N -D -5

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